http://rdf.ncbi.nlm.nih.gov/pubchem/patent/JP-2022088794-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_95eaed79dec59391549e8016815b3a8f |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-50 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-483 |
| filingDate | 2020-12-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1e9319f08ce37a64b0f8fa2552fc830d http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_84e78cacebff29830ce6716c4b09f0c8 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_571792d56fbde255fbafe3864e061963 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_a36236d53a874c16802bff06dd9c55a4 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f70558a35b8d7bbd81fb23ed5f64674c |
| publicationDate | 2022-06-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | JP-2022088794-A |
| titleOfInvention | Fatigue state estimation model learning method |
| abstract | PROBLEM TO BE SOLVED: To provide a learning method of a fatigue state estimation model capable of accurately estimating a user's fatigue state and the like. In a learning method in which a model parameter of a fatigue state estimation model is learned by an information processing device, the information processing device has an image of at least a part of the stratum corneum cells and a plurality of stratum corneum cells. Acquire teacher image data, which is an image configured to satisfy at least one of the conditions, and use the teacher image data to learn the model parameters of the fatigue state estimation model by a predetermined supervised machine learning algorithm. To execute. [Selection diagram] Fig. 2 |
| priorityDate | 2020-12-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 338.